Abstract
How global warming and agriculture mutually influence each other? It is possible to answer the question by searching knowledge about the relation between global warming and agriculture. As exemplified by this question, strong demands exist for searching relations between objects. However, methods or systems for searching relations are not well studied. In this paper, we propose a relation search system named “Enishi.” Enishi supplies a wealth of diverse multimedia information for deep understanding of relations between two objects by complementarily utilizing knowledge from Wikipedia and the Web. Enishi first mines elucidatory objects constituting relations between two objects from Wikipedia. We then propose new approaches for Enishi to search more multimedia information about relations on the Web using elucidatory objects. Finally, we confirm through experiments that our new methods can search useful information from the Web for deep understanding of relations.
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Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proc. of 16th WWW, pp. 697–706 (2007)
Zhang, X., Asano, Y., Yoshikawa, M.: Analysis of implicit relations on Wikipedia: Measuring strength through mining elucidatory objects. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds.) DASFAA 2010. LNCS, vol. 5981, pp. 460–475. Springer, Heidelberg (2010)
Zhang, X., Asano, Y., Yoshikawa, M.: Mining and explaining relationships in Wikipedia. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds.) DEXA 2010, Part II. LNCS, vol. 6262, pp. 1–16. Springer, Heidelberg (2010)
Zhu, J., Nie, Z., Liu, X., Zhang, B., Wen, J.R.: Statsnowball: a statistical approach to extracting entity relationships. In: Proc. of 18th WWW, pp. 101–110 (2009)
Bollegala, D., Matsuo, Y., Ishizuka, M.: Relational duality: unsupervised extraction of semantic relations between entities on the web. In: Proc. of 19th WWW, pp. 151–160 (2010)
Wayne, K.D.: Generalized Maximum Flow Algorithm. PhD thesis, Cornell University, New York, U.S (January 1999)
Nakayama, K., Hara, T., Nishio, S.: Wikipedia mining for an association web thesaurus construction. In: Benatallah, B., Casati, F., Georgakopoulos, D., Bartolini, C., Sadiq, W., Godart, C. (eds.) WISE 2007. LNCS, vol. 4831, pp. 322–334. Springer, Heidelberg (2007)
Koren, Y., North, S.C., Volinsky, C.: Measuring and extracting proximity in networks. In: Proc. of 12th ACM SIGKDD Conference (2006)
Weikum, G., Kasneci, G., Ramanath, M., Suchanek, F.: Database and information-retrieval methods for knowledge discovery. Commun. ACM 52(4), 56–64 (2009)
Kasneci, G., Suchanek, F.M., Ifrim, G., Ramanath, M., Weikum, G.: Naga: Searching and ranking knowledge. In: Proc. of 24th ICDE, pp. 953–962 (2008)
Taneva, B., Kacimi, M., Weikum, G.: Gathering and ranking photos of named entities with high precision, high recall, and diversity. In: Proceedings of 3rd WSDM, pp. 431–440. ACM, New York (2010)
Milne, D.N., Witten, I.H., Nichols, D.M.: A knowledge-based search engine powered by Wikipedia. In: Proc. of 16th CIKM, pp. 445–454. ACM, New York (2007)
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Zhang, X., Asano, Y., Yoshikawa, M. (2010). Enishi: Searching Knowledge about Relations by Complementarily Utilizing Wikipedia and the Web. In: Chen, L., Triantafillou, P., Suel, T. (eds) Web Information Systems Engineering – WISE 2010. WISE 2010. Lecture Notes in Computer Science, vol 6488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17616-6_43
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DOI: https://doi.org/10.1007/978-3-642-17616-6_43
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